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Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface.

Authors :
Xie, Jun
Xu, Guanghua
Zhao, Xingang
Li, Min
Wang, Jing
Han, Chengcheng
Han, Xingliang
Source :
Frontiers in Neurorobotics; 1/24/2019, pN.PAG-N.PAG, 10p
Publication Year :
2019

Abstract

Neuroplasticity, also known as brain plasticity, is an inclusive term that covers the permanent changes in the brain during the course of an individual's life, and neuroplasticity can be broadly defined as the changes in function or structure of the brain in response to the external and/or internal influences. Long-term potentiation (LTP), a well-characterized form of functional synaptic plasticity, could be influenced by rapid-frequency stimulation (or "tetanus") within in vivo human sensory pathways. Also, stochastic resonance (SR) has brought new insight into the field of visual processing for the study of neuroplasticity. In the present study, a brain-computer interface (BCI) intervention based on rapid and repetitive motion-reversal visual stimulation (i.e., a "tetanizing" stimulation) associated with spatiotemporal visual noise was implemented. The goal was to explore the possibility that the induction of LTP-like plasticity in the visual cortex may be enhanced by the SR formalism via changes in the amplitude of visual evoked potentials (VEPs) measured non-invasively from the scalp of healthy subjects. Changes in the absolute amplitude of P1 and N1 components of the transient VEPs during the initial presentation of the steady-state stimulation were used to evaluate the LTP-like plasticity between the non-noise and noise-tagged BCI interventions. We have shown that after adding a moderate visual noise to the rapid-frequency visual stimulation, the degree of the N1 negativity was potentiated following an ~40-min noise-tagged visual tetani. This finding demonstrated that the SR mechanism could enhance the plasticity-like changes in the human visual cortex. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16625218
Database :
Complementary Index
Journal :
Frontiers in Neurorobotics
Publication Type :
Academic Journal
Accession number :
134276348
Full Text :
https://doi.org/10.3389/fnbot.2018.00082